Power System Optimization (eBook)

Large-scale Complex Systems Approaches

Haoyong Chen, Honwing Ngan, Yongjun Zhang (Autoren)

eBook Download: PDF

2017 | 1. Auflage
392 Seiten
Wiley (Verlag)
978-1-118-72477-4 (ISBN)

Infos

Haoyong Chen, Professor and Assistant Dean, School of Electric Power, South China Univ. of Technology, China. Chen is a Senior IEEE Member. He was the first to apply the cooperative co-evolutionary algorithm to power system unit commitment and expand it to the areas of power system optimal planning/operation, oligopolistic electricity market simulation and analysis. He has been working in this area since 1995 with his research mainly concentrating in the areas of power system planning/operation/control, electricity market modelling/simulation/analysis, and smart grids. Chen has been leading a couple of China national scientific and technology research projects. He has published over 30 peer-reviewed journal paper and 4 books in Chinese. He also works closely with Chinese power companies.

Dr. Yongjun Zhang, Associate Professor, School of Electric Power, South China Univ. of Technology, China. His main research fields include power system operation analysis and control, voltage and reactive power optimization, power system reliability and risk assessment and power system energy saving assessment and planning. He has published some well cited papers in the authoritative international and Chinese journals. In particular, he has many experiences in solving practical engineering problems concerning reactive power optimization.

Dr. Honwing Ngan, of Department of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong.

Autor

Haoyong Chen, South China University of Technology, P. R. China Honwing Ngan, Asia-Pacific Research Institute of Smart Grid and Renewable Energy, Hong Kong Yongjun Zhang, South China University of Technology, P. R. China

Inhalt

Cover 1
Title Page 5
Copyright 6
Dedication 7
Contents 13
Foreword 19
Preface 21
Acknowledgments 27
List of Figures 29
List of Tables 33
Acronyms 37
Symbols 41
Chapter 1 Introduction 43
1.1 Power System Optimal Planning 44
1.1.1 Generation Expansion Planning 45
1.1.2 Transmission Expansion Planning 47
1.1.3 Distribution System Planning 49
1.2 Power System Optimal Operation 50
1.2.1 Unit Commitment and Hydrothermal Scheduling 50
1.2.2 Economic Dispatch 54
1.2.3 Optimal Load Flow 56
1.3 Power System Reactive Power Optimization 58
1.4 Optimization in Electricity Markets 60
1.4.1 Strategic Participants' Bids 60
1.4.2 Market Clearing Model 62
1.4.3 Market Equilibrium Problem 63
Chapter 2 Theories and Approaches of Large-Scale Complex Systems Optimization 64
2.1 Basic Theories of Large-scale Complex Systems 65
2.1.1 Hierarchical Structures of Large-scale Complex Systems 66
2.1.2 Basic Principles of Coordination 69
2.1.3 Decomposition and Coordination of Large-scale Systems 70
2.2 Hierarchical Optimization Approaches 72
2.3 Lagrangian Relaxation Method 78
2.4 Cooperative Coevolutionary Approach for Large-scale Complex System Optimization 82
2.4.1 Framework of Cooperative Coevolution 83
2.4.2 Cooperative Coevolutionary Genetic Algorithms and the Numerical Experiments 85
2.4.3 Basic Theories of CCA 87
2.4.4 CCA's Potential Applications in Power Systems 88
Chapter 3 Optimization Approaches in Microeconomics and Game Theory 91
3.1 General Equilibrium Theory 93
3.1.1 Basic Model of a Competitive Economy 94
3.1.2 Walrasian Equilibrium 95
3.1.3 First and Second Fundamental Theorems of Welfare Economics 96
3.2 Noncooperative Game Theory 97
3.2.1 Representation of Games 97
3.2.2 Existence of Equilibrium 102
3.3 Mechanism Design 103
3.3.1 Principles of Mechanism Design 103
3.3.2 Optimization of a Single Commodity Auction 105
3.4 Duality Principle and Its Economic Implications 108
3.4.1 Economic Implication of Linear Programming Duality 108
3.4.2 Economic Implication of Duality in Nonlinear Programming 110
3.4.3 Economic Implication of Lagrangian Relaxation Method 113
Chapter 4 Power System Planning 118
4.1 Generation Planning Based on Lagrangian Relaxation Method 118
4.1.1 Problem Formulation 120
4.1.2 Lagrangian Relaxation for Generation Investment Decision 122
4.1.3 Probabilistic Production Simulation 127
4.1.4 Example 129
4.1.5 Summary 133
4.2 Transmission Planning Based on Improved Genetic Algorithm 133
4.2.1 Mathematical Model 135
4.2.2 Improvements of Genetic Algorithm 137
4.2.3 Example 138
4.2.4 Summary 143
4.3 Transmission Planning Based on Ordinal Optimization 145
4.3.1 Introduction 145
4.3.2 Transmission Expansion Planning Problem 146
4.3.3 Ordinal Optimization 149
4.3.4 Crude Model for Transmission Planning Problem 153
4.3.5 Example 154
4.3.6 Summary 162
4.4 Integrated Planning of Distribution Systems Based on Hybrid Intelligent Algorithm 163
4.4.1 Mathematical Model of Integrated Planning Based on DG and DSR 164
4.4.2 Hybrid Intelligent Algorithm 166
4.4.3 Example 167
4.4.4 Summary 171
Chapter 5 Power System Operation 173
5.1 Unit Commitment Based on Cooperative Coevolutionary Algorithm 173
5.1.1 Problem Formulation 174
5.1.2 Cooperative Coevolutionary Algorithm 175
5.1.3 Form Primal Feasible Solution Based on the Dual Results 180
5.1.4 Dynamic Economic Dispatch 182
5.1.5 Example 188
5.1.6 Summary 190
5.2 Security-Constrained Unit Commitment with Wind Power Integration Based on Mixed Integer Programming 191
5.2.1 Suitable SCUC Model for MIP 193
5.2.2 Selection of St and the Significance of Extreme Scenarios 196
5.2.3 Example 198
5.2.4 Summary 202
5.3 Optimal Power Flow with Discrete Variables Based on Hybrid Intelligent Algorithm 202
5.3.1 Formulation of OPF Problem 204
5.3.2 Modern Interior Point Algorithm (MIP) 205
5.3.3 Genetic Algorithm with Annealing Selection (AGA) 209
5.3.4 Flow of Presented Algorithm 211
5.3.5 Example 211
5.3.6 Summary 214
5.4 Optimal Power Flow with Discrete Variables Based on Interior Point Cutting Plane Method 215
5.4.1 IPCPM and Its Analysis 217
5.4.2 Improvement of IPCPM 222
5.4.3 Example 227
5.4.4 Summary 229
Chapter 6 Power System Reactive Power Optimization 231
6.1 Space Decoupling for Reactive Power Optimization 231
6.1.1 Multi-agent System-based Volt/VAR Control 232
6.1.2 Coordination Optimization Method 235
6.2 Time Decoupling for Reactive Power Optimization 240
6.2.1 Cost Model of Adjusting the Control Devices of Volt/VAR Control 244
6.2.2 Time-Decoupling Model for Reactive Power Optimization Based upon Cost of Adjusting the Control Devices 249
6.3 Game Theory Model of Multi-agent Volt/VAR Control 257
6.3.1 Game Mechanism of Volt/VAR Control During Multi-level Power Dispatch 259
6.3.2 Payoff Function Modeling of Multi-agent Volt/VAR Control 266
6.4 Volt/VAR Control in Distribution Systems Using an Approach Based on Time Interval 273
6.4.1 Problem Formulation 275
6.4.2 Load Level Division 276
6.4.3 Optimal Dispatch of OLTC and Capacitors Using Genetic Algorithm 278
6.4.4 Example 280
6.4.5 Summary 286
Chapter 7 Modeling and Analysis of Electricity Markets 289
7.1 Oligopolistic Electricity Market Analysis Based on Coevolutionary Computation 289
7.1.1 Market Model Formulation 291
7.1.2 Electricity Market Analysis Based on Coevolutionary Computation 294
7.1.3 Example 300
7.1.4 Summary 307
7.2 Supply Function Equilibrium Analysis Based on Coevolutionary Computation 307
7.2.1 Market Model Formulation 309
7.2.2 Coevolutionary Approach to Analyzing SFE Model 313
7.2.3 Example 315
7.2.4 Summary 325
7.3 Searching for Electricity Market Equilibrium with Complex Constraints Using Coevolutionary Approach 326
7.3.1 Market Model Formulation 328
7.3.2 Coevolutionary Computation 332
7.3.3 Example 334
7.3.4 Summary 343
7.4 Analyzing Two-Settlement Electricity Market Equilibrium by Coevolutionary Computation Approach 343
7.4.1 Market Model Formulation 345
7.4.2 Coevolutionary Approach to Analyzing Market Model 349
7.4.3 Example 351
7.4.4 Summary 360
Chapter 8 Future Developments 361
8.1 New Factors in Power System Optimization 362
8.1.1 Planning and Investment Decision Under New Paradigm 362
8.1.2 Scheduling/Dispatch of Renewable Energy Sources 363
8.1.3 Energy Storage Problems 364
8.1.4 Environmental Impact 365
8.1.5 Novel Electricity Market 365
8.2 Challenges and Possible Solutions in Power System Optimization 366
Appendix 370
A.1 Header File 370
A.2 Species Class 371
A.3 Ecosystem Class 377
A.4 Main Function 378
References 380
Index 395
EULA 403

Produkt-Details

• Erscheint lt. Verlag: 15.3.2017
• Sprache: englisch
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Themenwelt: Wirtschaft
• Schlagworte: Electrical & Electronics Engineering • Elektrotechnik u. Elektronik • Energie • Energietechnik • Energy • Power Technology & Power Engineering • Qualität • Qualität u. Zuverlässigkeit • Quality & Reliability • Systems Engineering & Management • Systemtechnik • Systemtechnik u. -management
• ISBN-10: 1-118-72477-1 / 1118724771
• ISBN-13: 978-1-118-72477-4 / 9781118724774